Tuina improves patellofemoral osteoarthritis by alleviating the degree of lateral patellar tilt: a correlation analysis based on a randomized controlled trial
Bibliographic record
Abstract
PURPOSE: Abnormal patellar alignment is closely linked to patellofemoral osteoarthritis (PFOA), with laterally tilted patellae often worsening pain. This study investigates the relationship between imaging parameter changes and pain levels by analyzing the effects of Tui Na (TN) and intra-articular hyaluronic acid injections (IAHA) intervention. METHODS: This study included 126 PFOA patients from Wangjing Hospital of the China Academy of Traditional Chinese Medicine, between October 8, 2022, and December 31, 2024. Participants were randomly assigned to the TN or IAHA group. The IAHA group received one injection per week for five weeks, while the TN group underwent three Tui Na sessions per week for four weeks. The Visual Analogue Scale (VAS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and patellar imaging indices (Lateral Patellar Displacement (LPD), Congruence Angle (CA), Lateral Patellofemoral Angle (LPFA), Patellofemoral Index (PFI)) were assessed before and one week after treatment. To investigate the correlation between imaging parameters and VAS scores, Spearman rank correlation analysis was applied to non-normally distributed data, with scatter plots used to elucidate trends in the association between pain and imaging parameters. A multiple linear regression model was constructed to assess the independent effects of imaging parameters on changes in VAS scores. RESULTS: Both TN and IAHA treatments significantly reduced VAS and WOMAC scores (p < 0.05). No significant difference was observed in VAS score improvements between the two groups (p > 0.05). However, the TN group showed a significantly greater improvement in WOMAC scores (p < 0.05). The TN group also exhibited better improvements in LPD and CA compared to the IAHA group (p < 0.05). Spearman's correlation showed no significant link between imaging indices and VAS scores (p > 0.05). Multiple regression analysis revealed that reductions in VAS scores were associated with decreases in LPD (β = 0.274, p = 0.038) and CA (β = 0.309, p = 0.033). CONCLUSION: Tui Na is as effective as IAHA in relieving pain in PFOA patients, potentially alleviating pain through reductions in LPD and CA. TRIAL REGISTRATION: Chinese Clinical Trial Registry(ChiCTR), ChiCTR2200059345, Registered on 28/04/2022, https://www.chictr.org.cn/showproj.html?proj=166395.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".